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International Conference on Quantum Technologies, Communications, Computing, Hardware and Embedded Systems Security (iQ-CCHESS)

Linear Bit-by-Bit Encoding and its Application

Daniel Mathews

Published Sep 15, 2023• 0 citations
Publisher

Abstract

In computer terminology, encoding is the process of placing a specific code or a sequence of characters (in the form of certain symbols, punctuation, numbers, or letters) into a specific format for storage or efficient transmission. Today, quantum computers have been pitched to deliver the computing power necessary to solve computationally complex problems, that are currently thought to be difficult for classical computers. With the arrival of quantum machine learning algorithms, it has become important to explore unique methods of encoding and compressing data with qubits. In this paper, we will explore the possibility of linear bit-by-bit data compression in the state vector of a multi-qubit system. We will achieve this, by looking at a brief introduction to the topic, a possible way by which we could encode bits in a state vector and whether this system of encoding can be applied to a real time system. We will also elaborate on a possible application through a proposed protocol for secure communication, and suggest a further line of discussion on this topic.

DOI
10.1109/iq-cchess56596.2023.10391580

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A quantum algorithm provides for the encoding of an exponentially large number of classical data bits by use of a smaller (polynomially large) number of quantum bits (qubits). The development of this algorithm was prompted by the need, heretofore not satisfied, for a means of entering real-world binary data into a quantum computer. The data format provided by this algorithm is suitable for subsequent ultrafast quantum processing of the entered data. Potential applications lie in disciplines (e.g., genomics) in which one needs to search for matches between parts of very long sequences of data. For example, the algorithm could be used to encode the N-bit-long human genome in only log2N qubits. The resulting log2N-qubit state could then be used for subsequent quantum data processing - for example, to perform rapid comparisons of sequences.
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